{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
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       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>user_id</th>\n",
       "      <th>phone</th>\n",
       "      <th>name</th>\n",
       "      <th>last_activity</th>\n",
       "      <th>inactive_day</th>\n",
       "      <th>total_send</th>\n",
       "      <th>received_msg</th>\n",
       "      <th>gender</th>\n",
       "      <th>TrueOrFalse</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>760</td>\n",
       "      <td>13608328484</td>\n",
       "      <td>Grace Leo</td>\n",
       "      <td>2017-04-20 11:19:14.050333</td>\n",
       "      <td>27.0</td>\n",
       "      <td>90</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>4904</td>\n",
       "      <td>18510862726</td>\n",
       "      <td>七七</td>\n",
       "      <td>2017-04-29 14:15:46.237450</td>\n",
       "      <td>17.0</td>\n",
       "      <td>26</td>\n",
       "      <td>9</td>\n",
       "      <td>female</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>6973</td>\n",
       "      <td>18600084953</td>\n",
       "      <td>Hazy</td>\n",
       "      <td>2017-04-24 12:20:00.697703</td>\n",
       "      <td>23.0</td>\n",
       "      <td>191</td>\n",
       "      <td>3</td>\n",
       "      <td>female</td>\n",
       "      <td>2</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>9541</td>\n",
       "      <td>18482189337</td>\n",
       "      <td>陈丽诗</td>\n",
       "      <td>2017-04-21 16:25:23.906003</td>\n",
       "      <td>25.0</td>\n",
       "      <td>14</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>3</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>12723</td>\n",
       "      <td>13980622513</td>\n",
       "      <td>Junaooo</td>\n",
       "      <td>2017-05-01 05:33:07.246708</td>\n",
       "      <td>16.0</td>\n",
       "      <td>156</td>\n",
       "      <td>1</td>\n",
       "      <td>female</td>\n",
       "      <td>4</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   user_id        phone       name               last_activity  inactive_day  \\\n",
       "0      760  13608328484  Grace Leo  2017-04-20 11:19:14.050333          27.0   \n",
       "1     4904  18510862726         七七  2017-04-29 14:15:46.237450          17.0   \n",
       "2     6973  18600084953       Hazy  2017-04-24 12:20:00.697703          23.0   \n",
       "3     9541  18482189337        陈丽诗  2017-04-21 16:25:23.906003          25.0   \n",
       "4    12723  13980622513    Junaooo  2017-05-01 05:33:07.246708          16.0   \n",
       "\n",
       "   total_send  received_msg  gender  TrueOrFalse  \n",
       "0          90             1  female            0  \n",
       "1          26             9  female            1  \n",
       "2         191             3  female            2  \n",
       "3          14             1  female            3  \n",
       "4         156             1  female            4  "
      ]
     },
     "execution_count": 16,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# pandas读取excel数据示例\n",
    "# 【2016-7-30】 参考：十分钟搞定pandas：http://www.cnblogs.com/chaosimple/p/4153083.html\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "#df = pd.read_excel('C:\\Users\\warren\\Desktop\\warren.xlsx',index='time')\n",
    "#df = pandas.read_excel(open('your_xls_xlsx_filename','rb'), sheetname='Sheet 1')\n",
    "data_file = '../data/female_text.txt'\n",
    "#df = pd.read_table(data_file, sep=',')\n",
    "df = pd.read_csv(data_file)\n",
    "#df.index # 行序号\n",
    "df.head()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 17,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>name</th>\n",
       "      <th>phone</th>\n",
       "      <th>gender</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>Grace Leo</td>\n",
       "      <td>13608328484</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>七七</td>\n",
       "      <td>18510862726</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>Hazy</td>\n",
       "      <td>18600084953</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>陈丽诗</td>\n",
       "      <td>18482189337</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Junaooo</td>\n",
       "      <td>13980622513</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>慧慧</td>\n",
       "      <td>13716731756</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>鹅蛋脸女生</td>\n",
       "      <td>13433448936</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>Li可爱多</td>\n",
       "      <td>15712594823</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>Hope</td>\n",
       "      <td>18468062185</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>鱼儿</td>\n",
       "      <td>18811395085</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>请给我起一个英文名字</td>\n",
       "      <td>18210385540</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>Ceci</td>\n",
       "      <td>18611467993</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>七</td>\n",
       "      <td>13765277000</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>美元</td>\n",
       "      <td>15982440712</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>14</th>\n",
       "      <td>taurusxxx</td>\n",
       "      <td>13913939874</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>15</th>\n",
       "      <td>哈哈哈哈</td>\n",
       "      <td>13699455046</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>16</th>\n",
       "      <td>Nyxxxx</td>\n",
       "      <td>15810639686</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>17</th>\n",
       "      <td>王女口月</td>\n",
       "      <td>15972707824</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>18</th>\n",
       "      <td>Mira</td>\n",
       "      <td>18600411577</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>19</th>\n",
       "      <td>白小白</td>\n",
       "      <td>15821138172</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>20</th>\n",
       "      <td>南柯一梦</td>\n",
       "      <td>13699950092</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>21</th>\n",
       "      <td>one</td>\n",
       "      <td>18611810754</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>22</th>\n",
       "      <td>f</td>\n",
       "      <td>13349884208</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>23</th>\n",
       "      <td>Tomodezjcwon</td>\n",
       "      <td>18658187976</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>24</th>\n",
       "      <td>大脸猫</td>\n",
       "      <td>15671147752</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25</th>\n",
       "      <td>还没想好艺名</td>\n",
       "      <td>18670812169</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>26</th>\n",
       "      <td>电露泡影</td>\n",
       "      <td>15539144047</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>27</th>\n",
       "      <td>梦女孩小乔莺哟</td>\n",
       "      <td>15101043814</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>28</th>\n",
       "      <td>晨晨ccccccccc</td>\n",
       "      <td>18587195193</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>29</th>\n",
       "      <td>城城大人</td>\n",
       "      <td>15100705822</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>...</th>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "      <td>...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>71</th>\n",
       "      <td>三三</td>\n",
       "      <td>13671985368</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>72</th>\n",
       "      <td>张小逗</td>\n",
       "      <td>18755096214</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>73</th>\n",
       "      <td>悦悦</td>\n",
       "      <td>15840545492</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>74</th>\n",
       "      <td>于希</td>\n",
       "      <td>15806673672</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75</th>\n",
       "      <td>是我不好</td>\n",
       "      <td>13091017992</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>76</th>\n",
       "      <td>阿拉拉</td>\n",
       "      <td>13973287227</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>77</th>\n",
       "      <td>WANG</td>\n",
       "      <td>18600063427</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>78</th>\n",
       "      <td>molly</td>\n",
       "      <td>13568843543</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>79</th>\n",
       "      <td>美丽瓶</td>\n",
       "      <td>18222966910</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>80</th>\n",
       "      <td>小姐姐</td>\n",
       "      <td>13827843077</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>81</th>\n",
       "      <td>别看了 也不是你的</td>\n",
       "      <td>15011208368</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>82</th>\n",
       "      <td>Kelly Lee</td>\n",
       "      <td>15234399588</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>83</th>\n",
       "      <td>兔兔</td>\n",
       "      <td>15191023096</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>84</th>\n",
       "      <td>Summer</td>\n",
       "      <td>15911041181</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>85</th>\n",
       "      <td>kathryn</td>\n",
       "      <td>18612609223</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>86</th>\n",
       "      <td>雪儿</td>\n",
       "      <td>7789260839</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>87</th>\n",
       "      <td>对我就是小明</td>\n",
       "      <td>18622670726</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>88</th>\n",
       "      <td>豆沙</td>\n",
       "      <td>18607419881</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>89</th>\n",
       "      <td>Endicy</td>\n",
       "      <td>18487360924</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>90</th>\n",
       "      <td>Ood</td>\n",
       "      <td>13540214422</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>91</th>\n",
       "      <td>Y</td>\n",
       "      <td>13810683406</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>92</th>\n",
       "      <td>W</td>\n",
       "      <td>18310459910</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>93</th>\n",
       "      <td>六宫粉黛无颜色</td>\n",
       "      <td>18116218950</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>94</th>\n",
       "      <td>摩羯座</td>\n",
       "      <td>15500648023</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>95</th>\n",
       "      <td>文文</td>\n",
       "      <td>18792697326</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>96</th>\n",
       "      <td>mary</td>\n",
       "      <td>15044309838</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>97</th>\n",
       "      <td>男男</td>\n",
       "      <td>15541005019</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>98</th>\n",
       "      <td>popcern</td>\n",
       "      <td>18710233169</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>99</th>\n",
       "      <td>gg</td>\n",
       "      <td>18221125389</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>100</th>\n",
       "      <td>四月天</td>\n",
       "      <td>18833634100</td>\n",
       "      <td>female</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "<p>101 rows × 3 columns</p>\n",
       "</div>"
      ],
      "text/plain": [
       "             name        phone  gender\n",
       "0       Grace Leo  13608328484  female\n",
       "1              七七  18510862726  female\n",
       "2            Hazy  18600084953  female\n",
       "3             陈丽诗  18482189337  female\n",
       "4         Junaooo  13980622513  female\n",
       "5              慧慧  13716731756  female\n",
       "6           鹅蛋脸女生  13433448936  female\n",
       "7           Li可爱多  15712594823  female\n",
       "8            Hope  18468062185  female\n",
       "9              鱼儿  18811395085  female\n",
       "10     请给我起一个英文名字  18210385540  female\n",
       "11           Ceci  18611467993  female\n",
       "12              七  13765277000  female\n",
       "13             美元  15982440712  female\n",
       "14      taurusxxx  13913939874  female\n",
       "15           哈哈哈哈  13699455046  female\n",
       "16         Nyxxxx  15810639686  female\n",
       "17           王女口月  15972707824  female\n",
       "18           Mira  18600411577  female\n",
       "19            白小白  15821138172  female\n",
       "20           南柯一梦  13699950092  female\n",
       "21            one  18611810754  female\n",
       "22              f  13349884208  female\n",
       "23   Tomodezjcwon  18658187976  female\n",
       "24            大脸猫  15671147752  female\n",
       "25         还没想好艺名  18670812169  female\n",
       "26           电露泡影  15539144047  female\n",
       "27        梦女孩小乔莺哟  15101043814  female\n",
       "28    晨晨ccccccccc  18587195193  female\n",
       "29           城城大人  15100705822  female\n",
       "..            ...          ...     ...\n",
       "71             三三  13671985368  female\n",
       "72            张小逗  18755096214  female\n",
       "73             悦悦  15840545492  female\n",
       "74             于希  15806673672  female\n",
       "75           是我不好  13091017992  female\n",
       "76            阿拉拉  13973287227  female\n",
       "77           WANG  18600063427  female\n",
       "78          molly  13568843543  female\n",
       "79            美丽瓶  18222966910  female\n",
       "80            小姐姐  13827843077  female\n",
       "81      别看了 也不是你的  15011208368  female\n",
       "82      Kelly Lee  15234399588  female\n",
       "83             兔兔  15191023096  female\n",
       "84         Summer  15911041181  female\n",
       "85        kathryn  18612609223  female\n",
       "86             雪儿   7789260839  female\n",
       "87         对我就是小明  18622670726  female\n",
       "88             豆沙  18607419881  female\n",
       "89         Endicy  18487360924  female\n",
       "90            Ood  13540214422  female\n",
       "91              Y  13810683406  female\n",
       "92              W  18310459910  female\n",
       "93        六宫粉黛无颜色  18116218950  female\n",
       "94            摩羯座  15500648023  female\n",
       "95             文文  18792697326  female\n",
       "96           mary  15044309838  female\n",
       "97             男男  15541005019  female\n",
       "98        popcern  18710233169  female\n",
       "99             gg  18221125389  female\n",
       "100           四月天  18833634100  female\n",
       "\n",
       "[101 rows x 3 columns]"
      ]
     },
     "execution_count": 17,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "df.columns # 列名\n",
    "#df['lon'],df['lat'],df[:30] # 按照列名读取数据\n",
    "#df.ix[:30,:3] # 使用ix、loc或者iloc(按照下标组合)进行行列双向读取，即切片操作\n",
    "#df.ix[:20,['lon','lat']] # 跨属性组合选取\n",
    "df.loc[:100,['name','phone','gender']] # 同上\n",
    "#new = df.iloc[:20,[1,2]]\n",
    "#new.describe # 基本统计信息\n",
    "#type(new)\n",
    "#df[df.lon>117] # 按照数值过滤筛选\n",
    "#df[df.time<'2016-07-20']\n",
    "#new.values.tolist() # DataFrame转成list结构\n",
    "#df.sort(columns='time') # 排序"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "import numpy as np\n",
    "dir(np)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "# encoding:utf8\n",
    "import pandas as pd\n",
    "import numpy as np\n",
    "\n",
    "if __name__ == '__main__':\n",
    "    count = 0\n",
    "    for line in file('C:\\Users\\warren\\Desktop\\warren.csv'):\n",
    "        \"\"\" 处理数据\"\"\"\n",
    "        #if count > 10:\n",
    "        #    break\n",
    "        #print line\n",
    "        #count += 1\n",
    "        arr = [i.strip() for i in line.strip().split(',')]\n",
    "        if len(arr) < 5:\n",
    "            continue\n",
    "        print arr"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {
    "slideshow": {
     "slide_type": "slide"
    }
   },
   "outputs": [
    {
     "data": {
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7xthdKfj+/M5/MkZ3WwFjbHY6napLZ8NAnlQCkLNsDmIIqIyk/NuCo++ZmTZB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\nEI64+3e1GUBG2hXWe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vcTgTHeVpOaAkpdy8Xs6UfRXcvwTXGl+uaC53IPganPnAGqSl6H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\nTkSuQmCC\n",
      "text/plain": [
       "<IPython.core.display.Image object>"
      ]
     },
     "execution_count": 1,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import numpy as np \n",
    "from scipy.ndimage import filters \n",
    "import io \n",
    "import matplotlib \n",
    "import matplotlib.image as mpimg \n",
    "img = np.zeros((300, 300)) \n",
    "img[np.random.randint(0, 300, 1000), np.random.randint(0, 300, 1000)] = 255 \n",
    "img2 = filters.gaussian_filter(img, 4, order=2) \n",
    "\n",
    "import io \n",
    "import matplotlib # 导入画图包\n",
    "import matplotlib.image as mpimg \n",
    "from IPython import display \n",
    "buf = io.BytesIO() \n",
    "matplotlib.image.imsave(buf, img2, cmap=\"gray\") \n",
    "display.Image(buf.getvalue()) "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {
    "collapsed": true
   },
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "celltoolbar": "Raw Cell Format",
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.6.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 1
}
